সেলকা

তথ্যসূত্র:

• কোড
• আলিঙ্গন মুখ

উত্তর_নির্বাচন_বিশ্লেষণ

TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:

ds = tfds.load('huggingface:selqa/answer_selection_analysis')

• বর্ণনা :

The SelQA dataset provides crowdsourced annotation for two selection-based question answer tasks, 
answer sentence selection and answer triggering.

• লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
• সংস্করণ : 1.1.0
• বিভাজন :

বিভক্ত	উদাহরণ
'test'	1590
'train'	5529
'validation'	785

• বৈশিষ্ট্য :

{
    "section": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "article": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "is_paraphrase": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "num_classes": 10,
        "names": [
            "MUSIC",
            "TV",
            "TRAVEL",
            "ART",
            "SPORT",
            "COUNTRY",
            "MOVIES",
            "HISTORICAL EVENTS",
            "SCIENCE",
            "FOOD"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "answers": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "candidates": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "q_types": {
        "feature": {
            "num_classes": 7,
            "names": [
                "what",
                "why",
                "when",
                "who",
                "where",
                "how",
                ""
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

উত্তর_নির্বাচন_পরীক্ষা

TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:

ds = tfds.load('huggingface:selqa/answer_selection_experiments')

• বর্ণনা :

The SelQA dataset provides crowdsourced annotation for two selection-based question answer tasks, 
answer sentence selection and answer triggering.

• লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
• সংস্করণ : 1.1.0
• বিভাজন :

বিভক্ত	উদাহরণ
'test'	19435
'train'	66438
'validation'	9377

• বৈশিষ্ট্য :

{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "candidate": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "0",
            "1"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

উত্তর_ট্রিগারিং_বিশ্লেষণ

TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:

ds = tfds.load('huggingface:selqa/answer_triggering_analysis')

• বর্ণনা :

The SelQA dataset provides crowdsourced annotation for two selection-based question answer tasks, 
answer sentence selection and answer triggering.

• লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
• সংস্করণ : 1.1.0
• বিভাজন :

বিভক্ত	উদাহরণ
'test'	1590
'train'	5529
'validation'	785

• বৈশিষ্ট্য :

{
    "section": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "article": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "is_paraphrase": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "num_classes": 10,
        "names": [
            "MUSIC",
            "TV",
            "TRAVEL",
            "ART",
            "SPORT",
            "COUNTRY",
            "MOVIES",
            "HISTORICAL EVENTS",
            "SCIENCE",
            "FOOD"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "q_types": {
        "feature": {
            "num_classes": 7,
            "names": [
                "what",
                "why",
                "when",
                "who",
                "where",
                "how",
                ""
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "candidate_list": {
        "feature": {
            "article": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "section": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "candidates": {
                "feature": {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "answers": {
                "feature": {
                    "dtype": "int32",
                    "id": null,
                    "_type": "Value"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

উত্তর_ট্রিগারিং_পরীক্ষা

TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:

ds = tfds.load('huggingface:selqa/answer_triggering_experiments')

• বর্ণনা :

The SelQA dataset provides crowdsourced annotation for two selection-based question answer tasks, 
answer sentence selection and answer triggering.

• লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
• সংস্করণ : 1.1.0
• বিভাজন :

বিভক্ত	উদাহরণ
'test'	59845
'train'	205075
'validation'	28798

• বৈশিষ্ট্য :

{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "candidate": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "0",
            "1"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}